U.S. patent number 9,909,901 [Application Number 14/876,400] was granted by the patent office on 2018-03-06 for systems and methods to manage and control renewable distributed energy resources.
This patent grant is currently assigned to MELROK, LLC. The grantee listed for this patent is MELROK, LLC. Invention is credited to Paul W. Donahue, Michel Roger Kamel.
United States Patent |
9,909,901 |
Kamel , et al. |
March 6, 2018 |
Systems and methods to manage and control renewable distributed
energy resources
Abstract
A system for analyzing energy usage measures one or more
parameters indicative of energy usage for a plurality of
sub-circuits, where the sampling rate for the measuring is
substantially continuous, and automatically transmits information
related to at least one of the measured parameters at a rate that
enables monitoring of current energy usage. The system further
detects a significant change in a measured parameter, determines
whether the significant change in the measured parameter is caused
by a change in energy usage, and automatically transmits
information related to the significant change in the measured
parameter caused by the change in energy usage after detecting the
significant change.
Inventors: |
Kamel; Michel Roger (Buena
Park, CA), Donahue; Paul W. (Newport Coast, CA) |
Applicant: |
Name |
City |
State |
Country |
Type |
MELROK, LLC |
Reno |
NV |
US |
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Assignee: |
MELROK, LLC (Reno, NV)
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Family
ID: |
47021993 |
Appl.
No.: |
14/876,400 |
Filed: |
October 6, 2015 |
Prior Publication Data
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Document
Identifier |
Publication Date |
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US 20160028275 A1 |
Jan 28, 2016 |
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Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
Issue Date |
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13452618 |
Apr 20, 2012 |
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61478446 |
Apr 22, 2011 |
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61483552 |
May 6, 2011 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H02J
3/381 (20130101); H02S 40/32 (20141201); H02J
3/383 (20130101); H02J 13/00002 (20200101); G01D
4/002 (20130101); H02S 50/00 (20130101); G06Q
10/10 (20130101); H02J 13/00034 (20200101); H02J
13/00022 (20200101); G05B 15/02 (20130101); H02J
13/0006 (20130101); G01R 21/133 (20130101); H02J
3/38 (20130101); G08C 19/00 (20130101); H02J
3/00 (20130101); Y04S 40/00 (20130101); Y04S
40/128 (20130101); Y02P 90/84 (20151101); H02J
13/00 (20130101); Y02E 60/00 (20130101); Y04S
20/30 (20130101); Y02B 70/34 (20130101); Y02E
60/7838 (20130101); Y02P 90/845 (20151101); Y02E
10/56 (20130101); Y04S 10/18 (20130101); H02J
13/0079 (20130101); H02J 13/0062 (20130101); H02J
13/00028 (20200101); Y04S 40/124 (20130101); H02J
13/00016 (20200101); Y02E 60/7869 (20130101); Y02P
80/20 (20151101) |
Current International
Class: |
G01D
4/00 (20060101); H02J 13/00 (20060101); H02S
50/00 (20140101); H02J 3/38 (20060101); G06Q
10/10 (20120101); G08C 19/00 (20060101); G01R
21/133 (20060101); G05B 15/02 (20060101); H02J
3/00 (20060101); H02S 40/32 (20140101) |
References Cited
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WO |
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|
Primary Examiner: Barnes-Bullock; Crystal J
Attorney, Agent or Firm: Knobbe, Martens, Olson & Bear,
LLP
Parent Case Text
INCORPORATION BY REFERENCE TO ANY PRIORITY APPLICATIONS
Any and all applications for which a foreign or domestic priority
claim is identified in the Application Data Sheet as filed with the
present application are hereby incorporated by reference under 37
CFR 1.57. Provisional Application No. 61/497,421, filed Jun. 15,
2011, titled "SYSTEM AND METHODS FOR THE INTEGRATED AND CONTINUOUS
DESIGN, SIMULATION, COMMISSIONING, REAL TIME MANAGEMENT,
EVALUATION, AND OPTIMIZATION OF FACILITIES" and Provisional
Application No. 61/564,219, filed Nov. 28, 2011, titled "ENERGY
SEARCH ENGINE METHODS AND SYSTEMS", are hereby incorporated herein
by reference in their entireties to be considered a part of this
specification.
Claims
What is claimed is:
1. A method to manage and control solar power generation systems,
the method comprising: receiving first digital data associated with
electrical energy generated by a solar power generator associated
with a facility, wherein the first digital data is received in
accordance with a first protocol, and further wherein the first
digital data is received at a first rate of at least once per
minute; receiving second digital data from a smart meter or one or
more submeters associated with the facility, wherein the second
digital data provides an indication of electrical energy associated
with at least a portion of the facility, wherein the second digital
data is received in accordance with a second protocol, and further
wherein the second digital data is received at a second rate of at
least once per minute; receiving weather-related data and
grid-related data over a wide area network, wherein the
weather-related data and the grid-related data are received in
accordance with a third protocol; and providing, based at least in
part on the first digital data, the second digital data, the
weather-related data, and the grid-related data, a control signal
to control an inverter that is operationally coupled to the solar
power generator, wherein the control signal is provided at a third
rate of at least once per minute.
2. The method of claim 1 wherein the weather-related data comprises
one or more of actual weather data, predicted weather data, and
solar irradiance data.
3. The method of claim 1 wherein the grid-related data comprises
one or more of grid loading data, grid capacity data, pricing data,
energy rates, grid condition data, and grid forecast data.
4. The method of claim 1 wherein the control comprises one or more
of pulse width modulation (PWM) control, digital control, and
analog control.
5. The method of claim 1 wherein the control signal comprises one
of a digital control signal and an analog control signal.
6. The method of claim 1 wherein the solar power generator is
configured to generate electrical energy for use by the at least a
portion of the facility.
7. The method of claim 6 wherein the indication of electrical
energy associated with the facility comprises an indication of
excess electrical energy when the solar power generator generates
more electrical energy than is used by the at least a portion of
the facility and comprises an indication of deficit electrical
energy when the solar power generator generates less electrical
energy than is used by the at least a portion of the facility.
8. The method of claim 1 further comprising receiving
energy-related data, wherein the energy-related data is received in
accordance with a fourth protocol, and further wherein the
energy-related data comprises one or more of environmental data,
fuel type, prior energy consumption, facility occupancy schedules,
BIM (Building Information Modeling) data, GIS (Geographic
Information System) data, facility data, equipment specification
data, equipment maintenance logs, and asset inventory data.
9. The method of claim 8 further comprising providing, based at
least in part on the first digital data, the second digital data,
the weather-related data, the grid-related data, and the
energy-related data, the control signal.
10. The method of claim 1 wherein, based at least in part on the
control signal, the electrical energy generated by the solar power
generator is shifted, shed, stored, or supplemented.
11. An apparatus to manage and control solar power generation
systems, the apparatus comprising: a first input/output (I/O)
module configured to receive first digital data associated with
electrical energy generated by a solar power generator associated
with a facility, wherein the first digital data is received in
accordance with a first protocol, and further wherein the first
digital data is received at a first rate of at least once per
minute; a second I/O module configured to receive second digital
data from a smart meter or one or more submeters associated with
the facility, wherein the second digital data provides an
indication of electrical energy associated with at least a portion
of the facility, wherein the second digital data is received in
accordance with a second protocol, and further wherein the second
digital data is received at a second rate of at least once per
minute; a communication port configured to receive weather-related
data and grid-related data over a wide area network, wherein the
weather-related data and the grid-related data are received in
accordance with a third protocol; and a third I/O module configured
to provide, based at least in part on the first digital data, the
second digital data, the weather-related data, and the grid-related
data, a control signal to control an inverter that is operationally
coupled to the solar power generator, wherein the control signal is
provided at a third rate of at least once per minute.
12. The apparatus of claim 11 wherein the weather-related data
comprises one or more of actual weather data, predicted weather
data, and solar irradiance data.
13. The apparatus of claim 11 wherein the grid-related data
comprises one or more of grid loading data, grid capacity data,
pricing data, energy rates, grid condition data, and grid forecast
data.
14. The apparatus of claim 11 wherein the control comprises one or
more of pulse width modulation (PWM) control, digital control, and
analog control.
15. The apparatus of claim 11 wherein the control signal comprises
one of a digital control signal and an analog control signal.
16. The apparatus of claim 11 wherein the solar power generator is
configured to generate electrical energy for use by the at least a
portion of the facility.
17. The apparatus of claim 16 wherein the indication of electrical
energy associated with the facility comprises an indication of
excess electrical energy when the solar power generator generates
more electrical energy than is used by the at least a portion of
the facility and comprises an indication of deficit electrical
energy when the solar power generator generates less electrical
energy than is used by the at least a portion of the facility.
18. The apparatus of claim 11 further comprising receiving
energy-related data, wherein the energy-related data is received in
accordance with a fourth protocol, and further wherein the
energy-related data comprises one or more of environmental data,
fuel type, prior energy consumption, facility occupancy schedules,
BIM (Building Information Modeling) data, GIS (Geographic
Information System) data, facility data, equipment specification
data, equipment maintenance logs, and asset inventory data.
19. The apparatus of claim 18 further comprising providing, based
at least in part on the first digital data, the second digital
data, the weather-related data, the grid-related data, and the
energy-related data, the control signal.
20. The apparatus of claim 11 wherein, based at least in part on
the control signal, the electrical energy generated by the solar
power generator is shifted, shed, stored, or supplemented.
Description
BACKGROUND
The alternating-current power grid was developed in the late
nineteenth century with features such as centralized unidirectional
electric power transmission and demand-driven control. In the
twentieth century, utilities inter-tied small local grids to form
larger and larger power grids, which lent to efficiencies of scale.
However, near the end of the twentieth century, the economies of
scale of power production were limited by difficulties in
propagating supply and demand price signals through the system,
environmental concerns about power production, and an increased
dependence on limited fossil fuel resources.
SUMMARY
Digital communications technology can be added to various tiers of
the power grid to create smart grids at the utility level, the
municipality level, the individual energy consumer level, and as
far as the circuit, device or appliance level that are able to
receive real-time energy data and react accordingly. Embodiments
are directed towards an energy management system that measures,
analyzes, communicates, and controls energy usage with two-way
energy information. Embodiments collect and analyze energy data
from electrical circuits and sensors, and communicate the energy
information to power grids, micro grids, electric circuits,
appliances, and devices for use by utilities, municipalities,
businesses, and individual consumers.
Other embodiments of the energy management system perform real time
continuous and automated digital measurement, analysis, and
communication of energy usage. External sensors, such as
temperature sensors, for example, provide additional energy-related
data. The energy management system additionally stores and reports
energy quality and metrics based on the analysis of the energy
measurement data, external sensor data, and information from power
utilities.
Further embodiments of the energy management system integrate at
least some of universally interoperable "smart grid envisioned"
digital energy measurement, energy use analysis, carbon footprint
analysis, greenhouse gas emission analysis, energy quality and
availability analysis, data correction algorithms, data reduction
algorithms, data encryption algorithms, data storage, data
communication, control of energy used, carbon footprints associated
with the energy used, energy generated, and greenhouse gas
emissions associated with the energy generated. Embodiments of the
energy management system interface with "a smart device" "a smart
appliance" "a smart building" "the smart grid", renewable energy
generators, and the like.
Certain embodiments relate to a method of measuring and analyzing
energy usage. The method comprises measuring one or more parameters
indicative of energy usage for a plurality of sub-circuits, where
the sampling rate for measuring is substantially continuous,
automatically transmitting information related to at least one of
the measured parameters at a reporting rate decoupled from the
sampling rate that enables monitoring of current energy usage,
detecting a significant change in a measured parameter, determining
whether the significant change in the measured parameter is caused
by a change in energy usage, and automatically transmitting,
independent of the sampling rate and the reporting rate,
information related to the significant change in the measured
parameter caused by the change in energy usage after detecting the
significant change.
According to a number of embodiments, the disclosure relates to a
system for analyzing energy usage. The system comprises a plurality
of energy measurement devices configured to measure one or more
parameters indicative of energy usage for a plurality of
sub-circuits, where the sampling rate for measuring is
substantially continuous, computer hardware including at least one
computer processor, and computer-readable storage including
computer-readable instructions that, when executed by the computer
processor, cause the computer hardware to perform operations
defined by the computer-executable instructions. The
computer-executable instructions include automatically transmitting
information related to at least one of the measured parameters at a
rate that enables monitoring of current energy usage, detecting a
significant change in a measured parameter, determining whether the
significant change in the measured parameter is caused by a change
in energy usage, and automatically transmitting information related
to the significant change in the measured parameter caused by the
change in energy usage after detecting the significant change.
Further embodiments relate to a system for measuring, analyzing,
and controlling energy usage of a facility or facility subsystem.
The system comprises a plurality of energy measurement devices
configured to measure one or more parameters indicative of energy
usage for a plurality of circuits, sub-circuits, or systems where a
sampling rate for measuring is substantially continuous, a
plurality of measurement devices configured to measure one or more
parameters indicative of the energy efficiency of systems, where a
sampling rate for measuring is substantially continuous, and a
plurality of measurement devices configured to measure one or more
parameters indicative of the environmental condition of systems and
facilities, wherein a sampling rate for measuring is substantially
continuous. The system further comprises computer hardware
including at least one computer processor, and computer-readable
storage including computer-readable instructions that, when
executed by the computer processor, cause the computer hardware to
perform operations defined by the computer-executable instructions.
The computer-executable instructions include automatically
transmitting information related to at least one of the measured
parameters at a rate that enables monitoring of current energy
efficiency, automatically obtaining relevant environmental
conditions including weather data, automatically determining
control sequence to maximize energy efficiency, automatically
determining demand reduction potential, automatically determining
control sequence to minimize demand usage at any time without
affecting operations and comfort, automatically transmitting
control commands to at least one system or equipment, detecting a
significant change in a measured parameter, determining whether the
significant change in the measured parameter is caused by a change
in energy usage, determining whether and the significant change in
the measured parameter caused a change in energy efficiency, and
automatically transmitting information related to the significant
change in the measured parameter caused by the change in energy
efficiency after detecting the significant change.
For purposes of summarizing the disclosure, certain aspects,
advantages and novel features of the inventions have been described
herein. It is to be understood that not necessarily all such
advantages may be achieved in accordance with any particular
embodiment of the invention. Thus, the invention may be embodied or
carried out in a manner that achieves or optimizes one advantage or
group of advantages as taught herein without necessarily achieving
other advantages as may be taught or suggested herein.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 illustrates a schematic diagram of energy usage including an
energy management system to measure, analyze, communicate and
control the energy usage, according to certain embodiments.
FIG. 2 illustrates an exemplary schematic diagram of an energy
management system, according to certain embodiments.
FIG. 3 illustrates a schematic diagram of the exemplary energy
management system of FIG. 2, according to certain embodiments
FIG. 4 is a schematic diagram showing a polarity correction device,
according to certain embodiments.
FIG. 5 is a flow chart of an exemplary data reduction and data
validation process, according to certain embodiments.
FIG. 6 is a flow chart of an exemplary energy data management
process, according to certain embodiments.
DETAILED DESCRIPTION
The features of the systems and methods will now be described with
reference to the drawings summarized above. Throughout the
drawings, reference numbers are re-used to indicate correspondence
between referenced elements. The drawings, associated descriptions,
and specific implementation are provided to illustrate embodiments
of the inventions and not to limit the scope of the disclosure.
FIG. 1 illustrates a schematic diagram of energy usage 100
including an energy management system 102 to measure, analyze,
communicate, and control the energy usage of a facility 104. Energy
entering the facility 104 can be of many forms, such as for
example, thermal, mechanical, electrical, chemical, light, and the
like. The most common forms are typically electricity or power,
gas, thermal mass (hot or cold air), and solar irradiance. The
electrical energy can be generated from traditional fossil fuels,
or alternate forms of power generation, such as solar cells, wind
turbines, fuel cells, any type of electrical energy generator, and
the like. Ambient weather conditions, such as cloudy days, or time
of day, such as nighttime, may be responsible for radiant energy
transfer (gains or losses). Facilities 104 can comprise one or more
buildings, residences, factories, stores, commercial facilities,
industrial facilities, one or more rooms, one or more offices, one
or more zoned areas in a facility, one or more floors in a
building, parking structures, stadiums, theatres, individual
equipment or machinery (motors, chillers, pumps, fans, elevators,
etc.), electric vehicles with energy and/or information flow, or
the like. In another embodiment, the energy management system 102
measures, analyzes, communicates, and controls the energy usage of
one or more electric circuits, appliances, devices, micro grids,
power grids, or the like associated with the facility 104.
The energy management system 102 measures energy parameters from
the energy entering and consumed in the facility 104. The energy
management system 102 additionally receives sensor signals from
sensors 106. The sensors 106 can comprise current sensors, voltage
sensors, EMF sensors, touch sensors, contact closures, capacitive
sensors, trip sensors, mechanical switches, torque sensors,
temperature sensors, air flow sensors, gas flow sensors, water flow
sensors, water sensors, accelerometers, vibration sensors, GPS,
wind sensors, sun sensors, pressure sensors, light sensors,
tension-meters, microphones, humidity sensors, occupancy sensors,
motion sensors, laser sensors, gas sensors (CO2, CO), speed sensors
(rotational, angular), pulse counters, and the like.
The energy management system communicates with third parties 108
directly, over local area networks, over the world wide web 110,
such as the Internet, over a smart grid, and the like. Third
parties are, for example, utility companies, building maintenance
personnel, other energy management systems, first responders,
emergency personnel, governmental energy agencies, equipment,
control systems, other facilities, information databases, software
systems, web services, equipment vendors, equipment technical
support personnel, administrators, managers, smart meters, circuit
breakers, machinery, equipment, vehicles, battery systems, power
generators, fuel cells, inverters, PV panels, RSS feeds, weather
stations, measurement devices with digital output, and the like.
The energy management system 102 transmits the measured energy
parameters, energy performance metrics, energy reports, energy
alerts, control commands, activity logs, electricity demand
reduction potential, demand reduction potential (electricity, gas,
water), demand reduction measurements (electricity, gas, water),
baseline energy information, peak energy information, energy duty
cycle, power quality information, the sensor signals, and the like,
to the third party 108. In addition, the energy management system
102 can receive additional energy data from the third party 108.
Examples of the additional data include environmental data, weather
forecast, fuel type, energy rates, grid loading, prior energy
consumption, facility occupancy schedules, BIM (Building
Information Modeling) data, GIS (Geographic Information System)
data, facility data, equipment specification data, equipment
maintenance logs, asset inventory data, and the like.
The energy management system 102 analyzes the measured energy
parameters, the sensor signals, and the additional data to provide
analyzed energy data and energy controls. The energy management
system 102 analyzes the data to calculate energy loads, determine
possible energy reductions, identify malfunctioning systems,
determine carbon footprints, calculate phase imbalance, calculate
power quality, calculate power capacity, calculate energy
efficiency metrics, calculate equipment duty cycles, calculate
energy load profiles, identify peak energy, determine wasted
energy, analyze root cause of wasted energy, identify losses due to
simultaneous heating and cooling, calculate overcooling, calculate
overheating, calculate schedule losses, calculate rate analysis,
calculate payback of energy improvement measures, calculate optimum
capacity and maximum payback of alternate energy sources, calculate
demand reduction potential, calculate energy forecast, and the
like. In an embodiment, energy management system 102 provides
energy control signals based at least in part on the analysis of
the measured energy parameters, the sensor signals, and the
additional third party data. In one embodiment, the energy control
signals are pulse width modulation (PWM) control signals to control
the loading of electrical circuits associated with to the facility
104. Other examples of energy control signals are, but not limited
to, relay interrupts, software interrupts, analog outputs, digital
outputs, frequency modulation, voltage modulation, current
clamping, wireless control (AM, FM, RF, Wi-Fi.TM., WiMax.TM.,
etc.), wired control (Ethernet.RTM., BACNET.RTM., ModBus.RTM.,
IonWorks.TM., etc.) and the like. In other embodiments, the energy
management system 102 transmits the analyzed energy data to the
third parties 108 through direct communications, over a local area
network, over the Internet, over a smart grid, and the like.
FIG. 2 illustrates an exemplary block diagram of an embodiment of
the energy management system 102. The energy management system 102
comprises one or more computers 202 and memory 204, and
communicates with one or more third parties 108 through a network
210.
The computers 202 comprise, by way of example, processors, Field
Programmable Gate Array (FPGA), System on a Chip (SOC), program
logic, or other substrate configurations representing data and
instructions, which operate as described herein. In other
embodiments, the processors can comprise controller circuitry,
processor circuitry, processors, general-purpose single-chip or
multi-chip microprocessors, digital signal processors, embedded
microprocessors, microcontrollers and the like. In an embodiment,
the processor is an ADE 7880 by Analog Devices, an ADE 5169 by
Analog Devices, or ADE 7953 by Analog Devices, and the like.
The memory 204 can comprise one or more logical and/or physical
data storage systems for storing data and applications used by the
processor 202. In an embodiment, the memory 204 comprises program
modules 212 and at least one data storage module 214. In an
embodiment, the data storage module includes at least one
database.
In certain embodiments, the network 210 can comprise a local area
network (LAN). In yet other embodiments, the network 210 can
comprise one or more of the following communication means:
internet, Internet, intranet, wide area network (WAN), home area
network (HAN), public network, smart grid, combinations of the
same, or the like. In other embodiments, the network 210 can be any
communication system including by way of example, telephone
networks, wireless data transmission systems, two-way cable
systems, customized computer networks, interactive television
networks, and the like. In addition, connectivity to the network
210 may be through, for example, TCP IP, Ethernet.RTM.,
ZigBee.RTM., BlueTooth.RTM., Power Line Carrier (PLC), WiFi.TM.,
WiMax.TM., ModBus.RTM., BACnet.RTM., GSM.RTM. (Global System for
Mobile Communication), GPRS (General Packet Radio Service),
combinations of the same, or the like.
In an embodiment, the memory 204 comprises an interface module,
such as a Graphic User Interface (GUI), or the like, to provide a
user interface to the energy management system 102 through
interface equipment 216. The interface equipment comprises, by way
of example, a personal computer, a display, a keyboard, a QWERTY
keyboard, 8, 16, or more segment LEDs, LCD panels, a display, a
smartphone, a mobile communication device, a microphone, a keypad,
a speaker, a pointing device, user interface control elements,
combinations of the same, and any other devices or systems that
allow a user to provide input commands and receive outputs from the
energy management system 102.
The energy management system 102 further comprises input/output
circuits 206 and analog to digital converter (ADCs) modules 208.
The input/output circuits 206 interface with electrical circuits
218, including motors, such as, for example, fans 220,
pumps/compressors 222, variable air volume (VAV) valves, elevators,
and the like, temperature sensors 224, light ballasts, light
switches, and other internal or external sensors 226 to provide
current or voltage matching, voltage or current level adjustment,
control signals, frequency adjustment, phase adjustment, or the
like. The input/output circuits 206, in an embodiment, scale the
electrical measurements and sensor data so that the energy
measurement and sensor data can be analyzed and stored by the
processor 202 and the memory 204. The input/output circuits 206 are
digital, analog, or combinations of analog and digital
circuits.
The ADC modules 208 interface with the electrical circuits 218,
220, 222 to convert the analog energy measurements to digital
values for further analysis and processing by the processor 202 and
memory 204.
FIG. 3 illustrates an embodiment of the energy management system
102 comprising the processor 202, memory 204, one or more
temperature sensor compensation modules 300, one or more sensor
compensation modules 302 for other sensors, one or more ADC modules
208, one or more polarity correction devices 304, one or more
multiplexing devices 338, and one or more phase ADC modules 306.
The memory 204 comprises the data storage module 214 and the
program modules 212. In an embodiment, the program modules 212
comprise an energy calculation module 308, a data gateway module
310, a data validation and reduction module 312, a data analysis
module 314, a data encryption module 316, a global positioning
system (GPS) module 318, a web server module 320, a human machine
interface module 322, a pulse width modulation (PWM) controller
module 324, and a communication module 326.
In an embodiment, the energy measurement system 102 measures
electrical parameters, such as voltage, current, line-to-line
voltage, line-to-line current, line to neutral voltage, line to
neutral current, total power, reactive power, active power,
fundamental and harmonic total energy per phase, fundamental and
harmonic reactive energy per phase, active energy per harmonic
frequency per phase, reactive energy per harmonic frequency per
phase, fundamental and harmonic active energy per phase, and the
like, of 1 to n electrical circuits or sub-circuits 218. In
addition, the measured parameter comprises, by way of example,
light intensity, rotational speed, linear speed, temperature,
vibration, carbon dioxide, pressure, motion, flow, acceleration,
voltage, current, sound, ultrasonic frequencies, and the like. The
electrical circuit 218 can be locally or remotely located from the
energy management system 102 and can measure voltages ranging from
0 volts in a de-energized state to up to approximately 600 VAC or
VDC in an energized state, and high speed voltage spikes to 4 kV.
The energy management system 102 measures electrical circuits 218
have various phase configurations, such as, for example, single
phase, split phase, three phase Delta, three phase Wye, and the
like. The energy management system 102 operates at voltages from 80
VAC to 600 VAC and multiple frequencies, such as, for example, 50
Hz, 60 Hz, and the like.
A measurement device 330 is associated with each electrical circuit
218 and acquires an analog measurement of the current, voltage, or
power in its associated electrical circuit 218. In an embodiment,
the measurement devices 330 couple directly into the facility's
power distribution system where electrical measurements can be
acquired internally from the main power distribution bars or
through a connection to a circuit breaker. In another embodiment,
measurement devices 330 can be embedded in the circuit breakers to
measure the voltage and current of the circuit 218 associated with
the circuit breaker.
In an embodiment, the measurement device 330 electrically couples
to the energy management system 102 by directly connecting the
output leads of the measurement device 330 to the energy management
system 102. In another embodiment, the measurement devices 330
communicate measured energy data from the circuit 218 to the energy
management system 102 and control signals from the energy
management system 102 to the circuit 218 via wireless, wired,
optical, or power line carrier (PLC) communications.
The measurement devices 330 can be powered from the pickup and
rectification of the electromagnetic fields associated with the
circuit 218, by an electrical connection to energized circuits with
or without re-chargeable battery backup, or the like. The
measurement devices 330 comprise, by way of example, Rogowski
coils, DC shunts, external digital current sensors, external analog
current sensors, clamp on current measuring toroid transformers
(CTs), shunt resistor modules in series with a circuit breaker,
combinations of the same, and the like.
In an embodiment, the measurement devices 330 comprise current
transformers 330. When the current in a circuit 218 is too high to
directly apply to measuring instruments, the current transformer
330 produces a reduced current approximately proportional to the
current in the circuit 218. The current transformer 330 also
isolates the measuring instrument from very high voltage that could
damage the measuring instrument if directly connected to the
circuit 218.
For each measured electrical circuit 218, the current transformer
330 electrically couples to the ADC module 208 through the polarity
correction device 304. The polarity correction device 304 provides
the correct polarity of the circuit 218 to the ADC 208 should the
current transformer 330 be installed incorrectly. For example, when
the current transformer 330 is installed incorrectly, such as by
reversing the +/- outputs of the current transformer 330 with
respect to the circuit 218 it is measuring, the phase of the
measurement can be approximately 180 degrees different from the
actual phase of the measured circuit 218.
FIG. 4 is a schematic diagram illustrating an embodiment of the
polarity correction device 304. As describe above, the current
transformer 330 electrically couples to the ADC module 208 through
the polarity correction device 304, for each circuit 208. The
energy management system 102 automatically corrects for the
polarity of the measured circuit 218 should the current transformer
330 be installed incorrectly by sending a control signal to the
polarity correction device 304. Polarity correction can also be
done via software in one or more of the energy calculation module
308, the data gateway module 310 or the data validation and
reduction module 312.
In the embodiment illustrated in FIG. 4, the polarity correction
device 304 comprises a latching double pole double throw switch
400. The switch 400 is wire for polarity-reversal by connecting the
second throw of the first switch (1, 2) to the first throw of the
second switch (2,1) and also by connecting the first throw of the
first switch (1,1) to the second throw of the second switch (2,2).
The switch 400 can be a hardware device, which may be internally
wired for polarity-reversal applications or implemented in the
modules 212.
The energy management system 102 automatically corrects the
polarity of the measured circuit 218 by controlling the position of
the switch 400. In an embodiment, the data validation and reduction
module 312 evaluates when the voltage phase from the phase ADC
module 306 and the current phase from the ADC module 208 for a
given measured circuit 218 are separated by more than approximately
90 degrees and less than approximately 270 degrees, and/or when the
measured energy is negative in the absence of power generation.
When this condition exists, the current transformer 330 is
incorrectly coupled to the circuit 218 and is measuring an
incorrect phase of the circuit 218. The data validation and
reduction module 312 transmits a control signal to the switch 400
or applies a software correction. The switch 400 receives the
control signal and switches the contacts to the alternate position,
thereby correcting the measured polarity.
Referring to FIG. 3, the output of the polarity correction device
304 comprises the measured signal from the measurement device 330
with the correct polarity. The output of the polarity correction
module 304 electrically couples to the input of the ADC module 208.
The electrical signals from the electrical circuits 218 are analog
signals that are continuous in time. The ADC module 208 samples the
analog electrical signal from the measurement device 330 at a
sampling rate and converts the analog measurements to digital
values for use by the processor 202 and program modules 212.
In an embodiment, the energy management system 102 measures and
analyzes energy data from the electrical circuit 222 comprising an
electric motor that is used for pumping water or fluids, or for
compressing a gas such as used for compressed air, compressed
oxygen, compressed nitrogen, a heating, ventilation, and air
conditioning (HVAC) system, or the like. Sensors 332 physically
attach or electrically couple to the motor/pump/compressor 222.
Examples of the sensors 332 are, but not limited to, an
accelerometer for measuring vibration, a thermocouple for measuring
temperature, the current transformer 330 and polarity correction
device 304 for measuring current and voltage that is supplied to
the motor 222 in 1 to n stages, and the like. Additionally, the
fluid flow rate of the motor/pump 222 or the gas pressure in the
motor/compressor 222 can be measured through direct flow
measurement, with an ultrasonic flow sensor, with a pressure gauge,
or the like. The output of the sensor 332 electrically couples to
the input of the ADC module 208. The ADC module 208 samples the
analog electrical signal from the sensors 332 at a sampling rate
and converts the analog measurements to digital values for use by
the processor 202 and the program modules 212.
In another embodiment, the energy management system 102 measures
and analyzes energy data from an electrical circuit 220 comprising
an electric motor that is connected to a fan to deliver air flow.
Sensors 334 physically attach or electrically couple to the
motor/fan 220. Examples of the sensors 334 are, but not limited to,
an accelerometer for measuring vibration, a thermocouple for
measuring temperature, the current transformer 330 and polarity
correction device 304 for measuring current and voltage that is
supplied to the motor/fan 220 in 1 to n stages, air flow sensors to
measure air flow from the motor/fan 220, and the like. The output
of the sensor 334 electrically couples to the input of the ADC
module 208. The ADC module 208 samples the analog electrical signal
from the sensors 334 at a sampling rate and converts the analog
measurements to digital values for use by the processor 202 and the
program modules 212.
In an embodiment, the ADC module 208 comprises an analog to digital
converter, such as, for example ADE 5169 by Analog Devices, or the
like, and at least one jumper. The jumper is field selectable to
measure the phase of the electric circuit 218 having one of various
possible phase configurations, such as single phase, split phase,
three-phase Delta, three-phase Wye, or the like. In another
embodiment, the ADC module 208 comprises an ADC, such as ADE 5169
by Analog Devices, for example, and the phase configuration and
association of the ADC module 208 with its respective phase voltage
can be performed by the program modules 212. Further, the data
sampling rate of the ADC module 208 can range from approximately 10
Hz to approximately 1 MHz. In one embodiment, more than one set of
phase voltages can be connected to the energy management system
102, such as voltage upstream and downstream of a transformer. The
phase configuration of the ADC module 208 can be referenced to any
of the voltage phases through modules 212.
In another embodiment, a high speed ADC module 208 is electrically
coupled in parallel to a low speed ADC module 208 included in an
ADE7880 by Analog Devices. The high speed ADC module 208 measures
high speed voltage transients while the ADE7880 ADC and
microprocessor measure the active and reactive energy
parameters.
The phase ADC module 306 electrically couples to electrical
circuits having phases A, B, C through resistive voltage dividers
(not shown) or step down transformers (not shown) to digitally
measure the voltage amplitude and phase information for the phases
A, B, C. The resistive dividers proportionally reduce the amplitude
of the electrical signal such that the signal level is compatible
with the input signal requirements of the phase ADC module 306.
The phase signals from the phases A, B, C are analog signals that
are continuous in time. The energy management system 102 is capable
of measuring three-phase, 3-wire Delta electrical connections and
measuring three-phase, 4-wire Wye electrical connections. For
example, a three-phase Delta power generation system transmits
power on a 3-wire system where the phase of the power on each wire
is separated in phase from the other wires by approximately 120
degrees. The energy management system 102 chooses one of the phases
as a reference point. In another example, a three-phase Wye power
generation system transmits power on a 4-wire system where three of
the wires carry electrical current with phases separated by
approximately 120 degrees from each other. The fourth wire is
neutral, which is the reference point. The phase ADC module 306
samples these analog electrical signals at a sampling rate and
converts the analog measurements to digital values for use by the
processor 202 and modules 212. Each ADC module 306 can be
referenced to any of the voltage phase by software selection and
use of modules 212. In an embodiment, voltage phases are measured
once in module 306.
In one embodiment, a high speed phase ADC module 306 is
electrically coupled in parallel to a low speed phase ADC module
306 included in an ADE7880 by Analog Devices. The high speed phase
ADC module 306 measures high speed voltage transients while the
ADE7880 ADC and microprocessor measure the active and reactive
energy parameters.
In an embodiment, the energy management system 102 can be used to
measure currents and voltages of circuits on two or more
three-phase voltage sources. The three-phase voltage sources are
connected to two or more phase ADC modules 306. The multiplexing
device 338 is used to reference each line voltage in the phase ADC
modules 306 to any other line voltage in any of the phase ADC
modules 306. The multiplexing device 338 is also used to reference
the phase angle of the current in any of the ADC modules 208 to the
phase angle in any of the line voltages in any of the phase ADC
module 306.
In another embodiment, the energy management system 102 can be used
to measure currents and voltages of circuits on two or more
three-phase voltage sources. The three-phase voltage sources are
connected to two or more phase ADC modules 306. The multiplexing
device 338 is used to reference each line voltage in the phase ADC
modules 306 to any other line voltage in any of the phase ADC
modules 306. The multiplexing device 338 is also used to reference
the phase angle of the current in any of the ADC modules 208 to the
phase angle in any of the line voltages in any of the phase ADC
modules 306.
In yet another embodiment, the multiplexing function of the
multiplexing device 338 occurs by software. The digitized voltage
and current waveforms are digitally multiplexed in real time using
an FPGA or a digital signal processor. The digital multiplexer is
used to reference the phase angle of any of the current ADC modules
208 to the phase angle of any of the voltage phase ADC modules
306.
In an embodiment, the phase ADC module 306 comprises an analog to
digital converter, such as, for example, ADE 5169 by Analog
Devices, or the like, and at least one jumper. The jumper is field
selectable to measure the phase A, B, C having one of various
possible phase configurations, such as single phase, split phase,
three-phase Delta, three-phase Wye, or the like. Further, the data
sampling rate of the phase ADC module 306 can range from
approximately 0.1 Hz to approximately 1 MHz.
In an embodiment, the energy management system 102 and its
sub-modules can be powered externally or internally through the
voltage connection in phase ADC module 306. In other embodiments,
external power can be from another energy management system 102, an
external AC/DC power supply, an external AC power, or the like.
The phase ADC module 306, and the ADC modules 208 for the
electrical circuits 218, 220, 222 couple to the memory 204 over a
system bus 336. The system bus 336 can include physical and logical
connections to couple the processor 202, the memory 204, the sensor
compensation 300, 302, and the ADC modules 208, 306 together and
enable their interoperability.
The digital measurement information collected by the phase ADC
module 306, the ADC modules 208 for the 1 to n electrical circuits
218, and the ADC modules 208 for the circuits 220, 222 is sent to
the energy calculation module 308. The energy calculation module
308 performs energy calculations on the digital measurement
information and provides calculated energy data. Examples of the
calculated energy data are, but not limited to, line-to-line and
line-to-current voltage, total power, active power, reactive power,
line-to-line and line-to-neutral current, power factor, fundamental
and harmonic total energy per phase, fundamental and harmonic total
energy for the sum of phases, fundamental and harmonic active
energy per phase, fundamental and harmonic active energy for the
sum of phases, fundamental and harmonic reactive energy per phase,
fundamental and harmonic reactive energy for the sum of phases,
frequency, harmonic frequency, gas usage, chilled water usage, hot
water usage, total energy usage, and the like.
The data gateway module 310 samples the measured energy data and
the calculated energy data by controlling the sampling rate of the
phase ADC module 306 and the ADC modules 208. The sampling rate
ranges from approximately 0.1 Hz to approximately 1 MHz, and is
preferably between approximately 1 kHz and approximately 20 kHz,
more preferably between approximately 5 kHz and approximately 18
kHz, and most preferably between approximately 1 kHz and
approximately 8 kHz. In another embodiment, the sampling rate
ranges from approximately 0.1 Hz to approximately 24 kHz, and is
preferably between approximately 1 kHz and approximately 10 kHz,
more preferably between approximately 10 kHz and approximately 15
kHz, and most preferably between approximately 10 kHz and
approximately 24 kHz. In an embodiment, the sampling rate is user
selectable by the user from the user interface equipment 216. The
data gateway module 310 sends the measured data and the calculated
energy data to the data validation and reduction module 312. In
another embodiment, the ADC sampling rate is decoupled from the
data reporting rate sent to the 3.sup.rd party. The ADC sampling
rate ranges from 10 kHz to 1 MHz. The data reporting (push) rate to
the 3.sup.rd party can be user selectable and can be specific to
data from each of the sensors 330, 332, 334, 226, 224.
The data validation and reduction module 312 receives the measured
data and the calculated energy data from the data gateway module
310. Further, the data validation and reduction module 312 compares
the measured data and the calculated energy data with prior data
samples and/or near-in-time data samples to insure that relevant
and accurate data is passed to the data storage module 214 and to
the data command and communication module 326. In an embodiment,
the data validation and reduction module 312 determines data
accuracy.
In another embodiment, the data validation and reduction module 312
reduces the quantity of measured energy data. This is important for
embodiments where multiple energy management systems 102 are each
acquiring measurement data at up to approximately 24 kHz from
multiple circuits 218, 220, 222 because data collection could
overload a network, such as the smart-grid, or even the
communication network 210, with data. In a further embodiment, the
data validation and reduction module 312 performs both data
reduction and correction.
In one embodiment, the data validation and reduction module 312
analyzes significant changes in a measured energy parameter. In an
embodiment, the significant change in the measured energy parameter
may be indicative of a change in energy usage, or may be corrupted
data. The data validation and reduction module 312 analyzes energy
spikes in the measured energy data to determine whether the spike
is a valid change in energy usage, noise, or corrupted data by
acquiring additional samples from the data gateway module 310 at
approximately the same time or near-in-time as the energy spike. If
the energy spike is a valid data measurement, the amplitude of the
later acquired sample will be proportional to the energy spike. If
the amplitude of the later acquired data is substantially different
than the energy spike, the data validation and reduction module 312
determines that the energy spike was caused by noise, and treats
the bad data as irrelevant and not worthy of being passed on for
storage or "push" or "pull" communication.
In an embodiment, if the significant change is relevant and
indicative of a change in energy usage, the energy management
system 102 automatically transmits or pushes information relating
to the significant change in the measured parameter within one hour
after the detected change occurs, preferably within 15 minutes
after the detected change occurs, more preferable within 1 minute
after the detected change occurs, and most preferably within one
second after the detected change occurs.
In one embodiment, the data validation and reduction module 312
reduces the quantity of measured energy data that will be reported
in substantially real time, stored in the data storage module 214,
pushed or automatically transmitted to a remote or cloud database
over the communication network 210, or pulled from a user inquiry.
The reduced quantity of energy data is based at least in part on
previously defined or user defined data filtering parameters, such
as, for example, the amount of change of measured or calculated
energy data, the rate of change of measured or calculated energy
data, a maximum threshold on any of the measured or analyzed data,
a minimum threshold on any of the measured or analyzed data, or the
like. Reducing the quantity of measured data enables the energy
measurement system 102 to use low, medium, or high speed data
communication channels over the network 210 to deliver real time or
near real time energy reporting for circuits 218, 220, 222 that are
being digitally sampled at a higher rate.
In an embodiment, the data filtering parameter is at least a 10%
change in the detected value of the parameter, where the change is
one of an increase or a decrease, where the parameter is a measured
or a calculated parameter, and where the change is between the
current value and the previous value of the parameter. More
preferably, the data filtering parameter is at least a 5% change,
and most preferably, the data filtering parameter is at least a 1%
change. In another embodiment, the data filtering parameter is at
least a 10% change in the detected parameter.
In another embodiment, the data filtering parameter is at least a
10% difference in the rate of change of a parameter, where the
change is one of an increase or a decrease, where the parameter is
a measured or a calculated parameter, and where the change is
between the detected current rate of change and the previous rate
of change of the parameter. More preferably, the data filtering
parameter is at least a 5% difference in the rate of change, and
most preferably, the data filtering parameter is at least a 1%
difference in the rate of change.
FIG. 5 is a flow chart of an exemplary data reduction and data
validation process 500 for the data validation and reduction module
312. In an embodiment, the process 500 reduces and validates the
data measured and/or calculated from at least one of the electrical
circuits 208, 220, 222. Beginning at block 502, the process 500
acquires an initial energy measurement M.sub.0 from the data
gateway module 310. At block 504, the process 500 acquires a next
energy measurement M.sub.1 from the data gateway module 310.
M.sub.0 and M.sub.1 are measurements of the same electrical
parameter but separated in time, with M.sub.0 occurring first in
time. In an embodiment, M.sub.0 and M.sub.1 are separated in time
by one or more time periods of the sampling rate of the ADC module
208.
At block 506, the process compares M.sub.0 and M.sub.1 and
determines whether M.sub.0 and M.sub.1 have approximately the same
value. In an embodiment, M.sub.0 and M.sub.1 are approximately
equal if M.sub.0 and M.sub.1 differ from each other no more than a
percentage of their value, which is user-determined. For example,
M.sub.0 and M.sub.1 could be considered to have approximately the
same value if they differ from each other by no more than 1%. In
another embodiment, M.sub.0 and M.sub.1 have approximately the same
value when M.sub.0=M.sub.1.
If M.sub.0 and M.sub.1 are approximately the same value, the
process 500 determines M.sub.1 is redundant data or data with
little value and sets M.sub.0 to M.sub.1 at block 512 without
storing M.sub.1. From block 512, the process 500 returns to block
504 and acquires the next measurement M.sub.1.
If M.sub.0 and M.sub.1 are not approximately the same value at
block 506, the process 500 moves to block 508 where the process 500
determines whether the values of M.sub.0 and M.sub.1 differ
significantly, as could be indicative of an energy spike in the
measured parameter 218, 220, 222. In an embodiment, M.sub.0 and
M.sub.1 differ significantly if M.sub.0 and M.sub.1 differ from
each other more than approximately a percentage of their value,
which is user-determined. For example, M.sub.0 and M.sub.1 could be
considered to differ significantly if they differ from each other
by more than 50%.
If M.sub.0 and M.sub.1 do not differ significantly, the process
determines that M.sub.1 is a valid data measurement and is not a
redundant data measurement and stores M.sub.1 in the data storage
module 214. At block 512, the process 500 sets M.sub.0 to M.sub.1
and returns to block 504, where it acquires the next measurement
M.sub.1.
If M.sub.0 and M.sub.1 differ significantly at block 508, the
process 500 moves to block 514 where at least one additional
measurement M.sub.2 is acquired. In an embodiment, the at least one
additional measurement M.sub.2 is acquired within 5 minutes of
detecting the significant change in the measured parameter, more
preferably within 1 minute, and most preferably within 10 msec.
At block 516, the process 500 determines whether M.sub.2 is
proportional to M.sub.1. M.sub.2 and M.sub.1 are measurements of
the same electrical parameter but separated in time with M.sub.1
occurring first in time. In an embodiment, M.sub.2 and M.sub.1 are
separated in time by one or more time periods of the sampling rate
of the ADC 208. In another embodiment, M.sub.2 is acquired
asynchronously with respect to M.sub.1. If the energy spike M.sub.1
is a valid data measurement, the amplitude of the later acquired
sample M.sub.2 will be approximately proportional to the amplitude
of the energy spike M.sub.1. In an embodiment, M.sub.2 is
approximately proportional to M.sub.1 if the ratio M.sub.2/M.sub.1
is approximately constant.
If M.sub.2 is approximately proportional to M.sub.1, then M.sub.1
is a valid data measurement and the process 500 moves to block 510.
At block 510, the process 500 stores M.sub.1 in the data storage
module 214. At block 512, the process 500 sets M.sub.0 to M.sub.1
and returns to block 504, where it acquires the next measurement
M.sub.1.
If M.sub.2 and M.sub.1 are not approximately proportional, M.sub.1
is most likely not a valid data measurement. The process 500
determines that the energy spike M.sub.1 was caused by noise and
treats the bad data as irrelevant and not worthy of being passed on
to the data storage module 214 or for push/pull communication. The
process returns to block 504 and acquires the next measurement
M.sub.1. Thus, the process 500 validates and reduces the measured
and calculated energy data.
Referring to FIG. 3, the data validation and reduction module 312
sends the validated and reduced energy data to the data analysis
module 314. The data analysis module 314 also receives and
processes data from 3.sup.rd party through data command and
communication module 326, and from data storage module 214. The
data analysis module 314 sends the validated and reduced energy
data, and/or results of energy analysis, efficiency analysis, usage
analysis, occupancy analysis, performance analysis, etc., to one or
more of the data storage module 214 for storage, the web server
module 312 for transmission over the Internet, the human interface
module 322 for review and manipulation by the user, and the data
command and communication module 326 for transmission over the
network 210.
In an embodiment, the data analysis module 314 receives an
indication from the data validation and reduction module 312 when
the voltage phase and the current phase from the ADC module 208
exhibits more than approximately 90 degrees and less than
approximately 270 degrees of phase differential. The data analysis
module 314 automatically identifies the correct phase that is
associated with the ADC module 208 and attaches this phase
information to the corresponding energy information from the
associated ADC module 208 in the data validation and reduction
module 312. The data analysis module 314 corrects the phase
selection settings for the ADC module 208 in energy calculation
module 308 so that the ADC module 208 is referenced to the correct
phase from the phase ADC module 306.
Further, the data analysis module 314 processes validated and
reduced energy data, sensor data, and external environmental and
facility use information to derive and deliver electric load,
device, and building management system/energy management system
(BMS/EMS) control signals that are used to reduce or increase the
electric energy in one or more specific circuits 218, 220, 222.
For example, the data analysis module 314 compares the measured
fluid flow rate or gas pressure to the energy used by the motor
222, the temperature of the motor 222, the belt tension of motor
222, the rotational speed of motor 222, and the vibration of the
motor 222. Efficiency factors and curves are then derived from a
comparison and analysis of these measured operating parameters and
design operational parameters. Motor specifications are obtained
from vendor data or BIM data through the data command and
communication module 108, the web server module 320 or the data
storage module 214. The efficiency factors are used to
automatically adjust the AC motor speed through a variable speed or
vector drive motor controller to derive and optimize energy use for
a required fluid flow rate or compressed gas rate. The measured
data and efficiency factors are also used to alert a 3.sup.rd party
through the data command and communication module 108 of any motor
malfunction or maintenance requirement. In the case of a DC motor
222, the PWM controller 324 is used to control the voltage to the
motor/pump/compressor 222.
In another example, the data analysis module 314 compares the data
from the sensor 334 and other sensor 226 and analytically derives
the air flow of the motor 220. Other sensor 226 may measure
upstream pressure, downstream pressure, motor parameters such as
speed and temperature. The data analysis module 314 further
compares the derived air flow to the motor efficiency and related
motor/fan operating parameters. This data is then used to
automatically adjust the AC motor speed and optimize its energy use
through a variable speed or vector drive motor controller to
deliver optimum energy use for a required air flow rate. In the
case of a DC motor/fan 220, the PWM controller 324 is used to
control the voltage to the motor/fan 220 for optimized
operation.
At least some of the external environmental information is provided
by the temperature sensor 224 which couples to the system bus 336
through the temperature compensation device 300, by one or more
3.sup.rd party which couples to the system bus 336 through the data
command and communication module 326, and by the other sensors 226
which couple to the system bus 336 through the other sensor
compensation device 302. The temperature compensation device 300
receives the temperature measurements from the temperature sensor
224 and scales the temperature measurements so that the temperature
data is compatible with the input requirements of the processor 202
and memory 204. In the embodiment illustrated in FIG. 3, the
temperature sensors 224 are remotely located from the energy
management system 102. In other embodiments, the temperature
sensors 224 are located on the energy management system 102. The
temperature measurements provide weather or time of day related
temperature information of the areas surrounding the facility 104,
temperature information of locations internal to the facility 104,
device temperature information of the device associated with the
circuit 218, 220, 222, and the like. In an embodiment, the
temperature compensation 300 comprises calibration compensation
look up tables to correctly utilize J or K thermocouple devices or
wired/wireless thermostats for external local or remote measurement
of temperature.
Likewise, the other sensor compensation device 302 receives the
sensor measurements from the other sensors 226 and scales the
sensor measurements so that the sensor data is compatible with the
input requirements of the processor 202 and memory or modules 204.
In the embodiment illustrated in FIG. 3, the other sensors 226 are
remotely located from the energy management system 102. In other
embodiments, the other sensors 224 are located on the energy
management system 102. The other sensors, can be, by way of example
and not limited to pressure sensors, light sensors, acceleration
sensors, tension meters, flow sensors, gas sensors, microphones,
humidity sensors, occupancy sensors, motion sensors, vibration
sensors, wind speed, heat sensors, gas spectrometers, laser
sensors, humidity sensors, and other environmental sensors such as
water flow, air flow, and gas flow, and the like. The sensor data
is analyzed to calculate energy loads, determine possible energy
reduction, identify malfunctioning systems, and the like.
Based on analyzing and comparing at least the validated and reduced
energy data, input from the sensors 224, 226, 332, 334, and input
from 3.sup.rd party module 108, the data analysis module 314
provides control signals for load control. In an embodiment, the
energy management system 102 comprises the analog input/output
ports 206 and/or the digital input/output ports 206, and the
control signals are delivered to external devices through the ports
206 for load control of the external devices. In another
embodiment, the control signals are delivered to the circuits 218,
220, 222 through the PWM controller module 324. In another
embodiment, the control signals are delivered to 3.sup.rd party
through the data command and communication module 326.
In an embodiment, the energy management system 102 couples to the
electrical circuits 218, 220, 222 through external high speed
electronic switches such as high power MOSFETs, IGFETs, or the
like. The PWM controller module 324 outputs a variable duty cycle
pulsed signal for load control to the external high speed
electronic switches. Such variable width pulses enable the external
high speed electronic switch to control the electric energy and
carbon footprint of any electric circuit 218, 220, 222 by switching
the power to the electric circuit ON and OFF at high frequencies
and for varying amount of time. The switching frequency varies from
several times a minute to several kHz. The variable duty cycle
pulsed signal in combination with the external high speed
electronic switch is associated with a Class D or Class E control
system design.
The data analysis module 314 sends the validated and reduced energy
data and the analyzed energy data to the data command and
communication module 326. The data command and communication module
326 interfaces the energy management system 102 to third parties
108 through the communication network 210. The data command and
communication module 326 pushes data and pulls data, where a data
push is a request for the transmission of information initiated by
the energy management system 102 (the sender) or an automatic
transmission, and a data pull is a request for the transmission of
information initiated by the third party 108 (the receiver).
The data command and communication module 326 can push the
validated and reduced energy data and/or the analyzed energy data
using protocols to a remote device for real time or near real time
analysis, to a remote device for control of the remote device, to a
remote structured query language (SQL), SAP, or cloud database for
storage, or the like. Further, the pushed data can be used for
comparison of data, data mining, and additional data analysis. The
additional data analysis includes but is not limited to billing,
control of circuits, control of smart appliances, control of
electric vehicle energy use, control of electric transportation
systems energy use, and the like.
Examples of the protocols and communication systems are, but not
limited to, Ethernet.RTM. such as IEEE standard 802.3, ZigBee.RTM.,
Power Line Carrier (PLC), WiFi.TM. such as the IEEE family of
standards 802.11, WiMax.TM. such as IEEE standard 802.16e-2005, and
GSM. The data can be delivered in, for example, XML, JSON, CSV,
ASCII strings, binary strings, and other formats. In an embodiment,
the data command and communication module 326 uses data clock
synchronization and system clocking via an Ethernet.RTM.
connection. Other system connections include networked TCP/IP,
client-server ModBus.RTM., BACnet.RTM., mesh network ZigBee.RTM.
wireless, WiFi.TM., WiMax.TM. that are operating either
individually or concurrently to interact with third party hardware
and software.
The data command and communication module 326 further can store one
or more of a copy of the measured data, the calculated data, the
validated and reduced energy data, the analyzed energy data, and
the sensor data in the data storage module 214 so that it can be
viewed and accessed through the web server 320 or data command and
communication module 326, according to certain embodiments. The
data storage module 214 can store data in any of the data storage
formats: binary, comma separated values, text file, XML files,
relational database or non-relational database.
In one embodiment, the data command and communication module 326
can be configured to act as a slave to an acquisition host of the
third party 108, such as a PC or the like, and can be configured to
communicate with a master host of the third party 108 in one of
several standard protocols, such as Ethernet.RTM., ModBus.RTM.,
BACnet.RTM., for example. The data command and communication module
326 then acts as a translation of the protocol to serial
communication.
In another embodiment, the energy management system 102 comprises a
software digital I/O module and an analog I/O module, which
interface with the data command and communication module 326 and
with the data analysis module 314 to enable two-way software
commands and interrupts between the data analysis module 314 and
Building Management Systems (BMS), Building Energy Management
Systems (BEMS), electrical vehicle charge stations, motor control
systems, electrical control systems, smart appliances, programmable
logic controllers, energy management reporting systems, carbon
footprint reporting systems, other energy management system 102,
and the like. In another embodiment, the I/O modules interface with
pulse counters from natural gas or water meters to integrate this
additional data.
The data command and communication module 326 implements
predetermined and automated power reduction steps in energy use
systems, smart appliances, or plug loads, based at least in part on
at least one of the measured energy data, the calculated energy
data, the reduced and validated energy data, the analyzed energy
data, the sensor data, data from another energy management system
102, or on external demand response commands, according to certain
embodiments.
The data storage module 214 stores energy data, such as the
measured energy data, the calculated energy data, the reduced and
validated energy data, the analyzed energy data, the sensor data,
and any other data received or created by the energy management
system 102. In an embodiment, the data storage module 214 provides
a data buffer in case the communication channel with a local or
remote host is broken. The buffer 214 decouples data sampling rates
and data reporting rates. The energy data is stored locally at the
required sampling rate until the communication lines are
re-established. The energy data is then transferred to the host
ensuring no data loss from a communication breakdown.
In an embodiment, the energy management system 102 records
measurements from sensors 330, 332, 226, 224 at sampling
frequencies larger than approximately 20 kHz. The measurements are
validated in the data validation and reduction module 312 and
analyzed in the data analysis module 314. The data command and
communication module 326 automatically transfers the data to the
third party 108 or the data storage module 214 at a reporting rate
of approximately once every 1 minute. The sampling rate and the
reporting rate are decoupled.
In another embodiment, the energy management system 102 records
measurements from sensors 330, 332, 226, 224 at a sampling
frequency of approximately 20 kHz. The measurements are validated
in the data validation and reduction module 312 and analyzed in the
data analysis module 314. The data command and communication module
326 automatically transfers the data to the third party 108 or the
data storage module 214 at a reporting rate of approximately once
every 1 minute. The measured data is compared to maximum and
minimum thresholds at the sampling frequency of approximately 20
kHz. The data that crosses a threshold is automatically transferred
to the third party 108 or the data storage module 214 at the time
the threshold is crossed, independent of the reporting rate. The
reporting of measured data at the rate of approximately once every
minute continues unabated.
In an embodiment, the data encryption module 316 encrypts the
energy data derived from measuring the electric circuits 218, 220,
222 using secure and anti-hacking data encryption algorithms. In
another embodiment, the data encryption module 316 uses anti-tamper
and anti-hacking handshaking from existing and emerging "smart
grid" and or IT security data protocols.
In an embodiment, each energy management system 102 further
comprises a unique address. In an embodiment, the address is a MAC
address. In another embodiment, the address is a Globally Unique
Identifier (GUID). In another embodiment, the unique identifier is
a combination of an address and GPS information. The GPS module 318
maps the location of each addressed energy management system 102
and sends the GPS location coordinates to the data and command
communication module 326, where the location coordinates are
associated with the energy measurement data from the addressed
energy management system 102. In an embodiment, the data encryption
module 316 encrypts the energy data and the location
information.
The human machine interface module (HMI) 322 provides an
interactive user interface between the interface equipment 216 and
the energy management system 102 over the communication bus 210.
The web server module 320 further interfaces with the HMI module
322 and/or the interface equipment 216 to further provide the user
with a Web-based user interface. In other embodiments, the energy
management system 102 further comprises a user interface software
module that is compatible with the ISO/IEEE 802/3 standard
(Ethernet.RTM.) from personal computers (PCs) on local area or wide
area networks.
The interface equipment 216 comprises, by way of example, a
personal computer, a display, a keyboard, a QWERTY keyboard, 8, 16,
or more segment LEDs or LCD panels, a display, a smartphone, a
mobile communication device, a microphone, a keypad, a speaker, a
pointing device, user interface control elements, tablet PCs,
combinations of the same, and any other devices or systems that
allow a user to provide input commands and receive outputs from the
energy management system 102.
In one embodiment, the user, through the user interface, can define
the grouping of sensors 330, 332, 334, 226, 224 to be measured and
analyzed, define the locations for the sensors 306, 304, 332, 226,
224 to be measured and analyzed. Analysis performed on information
from individual sensors 330, 332, 334, 224, 226 can also be
performed on any grouping of these sensors in quasi real time or
near real time. Groups may also include information from sensors
attached to other energy management system 102. In an embodiment,
the groupings and locations of the circuits 218 can be implemented
using "drag and drop" techniques. Grouping and location information
can be stored locally in data storage 214 and or in a remote data
base. In addition, the "drag and drop" techniques can be used for
charting and reporting. In another embodiment, the energy
management system 102 further comprises a mobile device module to
interface the energy management system 102 with a mobile device.
Users can view real time or stored and "pushed" or "pulled" energy
use on mobile platforms, such as for example, iPhone.RTM.,
Android.TM., BlackBerry.RTM., and the like.
Through the user interface, the user can define minimum and maximum
alert thresholds on measured and calculated energy metrics, such
as, for example, voltage, current, energies, energy consumption
rate, powers, power factor, cost, cost rate, energy efficiency
metric, energy efficiency rating, and the like, for each sensor
330, 332, 334, 224, 226, group of sensors 330, 332, 334, 224, 226
and locations.
Comparative alert thresholds are set for alerts triggered by
relative energy signatures and/or readings between sensors 330,
332, 334, 224, 226, groups of sensors 330, 332, 334, 224, 226, and
locations with each other, with established baselines, or with
established benchmarks. Predictive alert thresholds are set for
alerts triggered by the projected energy consumption and values of
energy sensors 330, 332, 334, 224, 226, groups of sensors 330, 332,
334, 224, 226, or location. When an alert, as defined by the user,
is triggered, the energy management system 102 provides the user
with an alert through email, text message, Facebook.RTM.,
Twitter.RTM., voicemail, RSS feeds, multi-media message automatic
alerts, and the like. In one embodiment, the alert is accompanied
by a description of the trigger event including charts and reports
on the energy history before the alert trigger, the projected
consumption, the results of the trigger event, and the like.
In another embodiment, through the web server module or the push
capability, the energy management system 102 provides the user with
animated and interactive desktop and mobile widgets for
communicating energy consumption levels, energy ratings and
critical energy conservation measures to end users. In another
embodiment, the energy management system 102 communicates energy
consumption levels, energy ratings, energy efficiency metrics, and
critical energy conservation measures to end users through RSS
feeds with desktop tickers.
In other embodiments, the energy management system 102 determines
and reports the need for equipment or system maintenance, such as,
for example, air filter replacement, fluid filter replacement, belt
tensioning, belt alignment, worn or damaged belt, worn or damaged
bearings, worn or damaged gears, poor lubrication, damaged anchor
or frame, damaged or worn brushes, unbalanced voltage, poor power
quality, distorted waveform, high harmonic distortion, poor power
factor, phase load imbalance, critical power capacity, defective
sensor, duct leak, pipe leak, worn insulation, defective power
capacitors, defective battery, defective power filter, defective
uninterruptable power supply (UPS), defective voltage regulator,
defective circuit breaker, defective economizer vanes, defective
air valves, defective gas valves, defective water valves, defective
meters, defective indicators, and the like, based on an electrical
signature from the measured, calculated and analyzed electrical
parameters, inputs from other sensors 226, 224, data from the
3.sup.rd party 108, and stored data from data storage 214. In an
embodiment, the electrical signature comprises at least one of a
current and/or voltage waveform, current and/or voltage levels and
peaks, power factor, other sensor information, such as temperature,
vibration, acceleration, rotation, speed, and the like, of any
"downstream" motor or pump.
FIG. 6 is a flow chart of an exemplary energy data management
process 600. Beginning at blocks 602 and 603, the process 600
acquires energy measurements and sensor measurements respectively.
In an embodiment, the measurements are acquired at a rate of up to
approximately 24 kHz.
In some embodiments, the bandwidth of the communications between
the energy management system 102 and third parties, over for
example, a LAN, an internet, the Internet, or the like, may be
insufficient to accommodate data at up to 24,000 samples per second
for 1 to n circuits 218, 220, 222 and 1 to n sensors 226 and 224.
To accommodate a smaller bandwidth, the process 600 at blocks 604
and 605 reduces the quantity of measurements stored and/or
transmitted by not saving a measurement that is approximately the
same as the prior measurement for each sensor 330, 332, 334, 224,
226 as described in FIG. 5 above. In an embodiment, the user
determines how much the next measurement and the previous
measurement differ before the measurements are not approximately
the same.
At blocks 606 and 607, the process 600 validates the reduced
measurements. When the next measurement differs significantly from
the previous measurement, the process 600 acquires additional
measurements of the parameter and compares the amplitudes of the
additional measurements with the amplitude of the significantly
different measurement, as described in FIG. 5 above. When the
amplitudes are not proportional, the differing measurement is
considered to have been caused by noise and it is not saved or
transmitted. Conversely, when the amplitudes are proportional, the
differing measurement is considered to be a valid measurement,
indicative of an energy usage event, and it is stored and/or
transmitted.
At block 610, the process 600 analyzes the acquired measurements,
the reduced measurements, and the validated measurements to provide
calculated energy measurements, energy efficiency metrics, energy
ratings, cost information, carbon footprint, maintenance list,
control signals, reports, recommendations, and the like. In an
embodiment, the analysis is based at least in part on the sensor
data.
At block 612, the process 600 communicates all or part of the
energy data, the reduced and validated energy data, and/or the
calculated energy data to third parties or to data storage 214. In
an embodiment, the process automatically transmits or pushes the
energy data directly to the third party, over a local area network,
over a wide area network, over a smart grid, over an internet, over
the Internet, or the like. The transmitted energy data comprises
control signals, reports, recommendations, or the like. In an
embodiment, the process 600 automatically transmits information
related to at least one measured parameter at a rate of at least
one per hour, more preferably at a rate of at least once per 15
minutes, and most preferably at a rate of at least once per minute.
In another embodiment, the rate of automatically transmitting
energy information may change based at least in part of the
variability of the measured parameter. In another embodiment, the
data is analyzed and transmitted at regular or user defined
intervals, in addition to when the data crosses a user defined
threshold. In another embodiment, the data from different sensors
330, 332, 334, 224, 226 is sampled and analyzed at different
intervals. In another embodiment, the data from different sensors
330, 332, 334, 224, 226 is reported at different intervals.
At block 614, in an embodiment, the process 600 transmits control
signal to at least one of the measured circuits 218, 220, 222, to
another energy management system 102, or to a 3.sup.rd party 108.
In an embodiment, the control signals are pulse width modulation
(PWM) signals to control the loading on the measured circuit 218,
220, 222. In an embodiment, the PWM signals are based at least in
part on the sensor data. In an embodiment, the PWM signals are
based at least in part on the measured energy data. In an
embodiment, the PWM signals are based at least in part on data from
the 3.sup.rd party 108. In another embodiment, the PWM signals are
based at least in part on the calculated energy data.
In an embodiment, the energy management system 102 can be used to
measure energy usage and energy efficiency parameters related to
the energy performance of electric motors. The acquire energy
measurements block 602 may include, for example, power, current,
voltage, power quality, harmonic energy, fundamental energy, energy
in each harmonic frequency, voltage sags, voltage spikes, current
drops, current spikes, and the like. The acquire sensor data block
603 may include, for example, motor vibration, motor speed, belt
tension, motor temperature, motor imbalance, motor torque,
parameters upstream motor, parameters downstream motor, and the
like. The third party 108 and the data storage 214 may include, for
example, facility demand reduction requirements, utility demand
reduction requirements, weather conditions, building occupancy
information, motor specifications from vendor, building information
modeling (BIM) data on building systems, and the like. The
communicate data block 612 may automatically transfer demand
reduction potential, motor efficiency metrics, motor maintenance
requirements, and motor maintenance alerts, motor activity log,
motor event log, projected motor energy usage, and the like. The
provide control signals block 614 includes, for example, pulse
width modulation control of motor power, motor speed control, motor
frequency control, turning motor ON, turning motor OFF, command
sequences to other energy management systems 102, command sequences
to third parties 108, and the like.
Additional Embodiments of the Energy Management System
In another embodiment, the energy management system 102 can be used
to monitor at substantially continuous sampling rates the power
quality of systems and report only power distortions independent of
the reporting rate of the energy parameters. The ADC module 208
measures current and voltage at sampling rates exceeding
approximately 20 kHz and compares the measured waveform of every
circuit 218 and voltage from the phase ADC modules 306 to an
acceptable waveform. The energy contained at each harmonic
frequency is compared to an acceptable level of energy at each
harmonic frequency in modules 212. The total harmonic energy, total
fundamental energy, and the ratio of harmonic to fundamental
energies are compared to acceptable levels in modules 212. The
measured waveforms that are not acceptable waveforms, distorted
waveforms, or in other words, fall out of specification, may be
stored in the data storage module 214 and/or communicated via the
data command and communication module 326. Alerts can be sent when
a waveform is out of specification through the data command and
communication module 326 within a user-defined period of time from
when the distorted waveform was detected. In an embodiment,
algorithms can be in place to avoid sending repeated alerts when
sequential waveforms are distorted or when distorted waveforms are
detected within a specified period of time. The ADC module 208 and
the phase ADC module 306 can be used to detect high frequency
spikes and drops in the measured parameters. Information on
detected spikes can be stored in the data storage module 214 or
transferred through the data command and communication module 326
at rates independent of the sampling rate or the reporting rate. A
log of power quality, a count of acceptable waveforms, a count of
non-acceptable waveforms, non-acceptable waveforms, spikes in
measured data, drops in measured data, and the like, can be kept in
the data storage module 214 and/or transferred through the data
command and communication module 326.
Embodiments of the system relate to a method of measuring and
analyzing energy usage. The method comprises measuring one or more
parameters indicative of energy usage for a plurality of
sub-circuits, wherein a sampling rate for measuring is
substantially continuous, automatically transmitting information
related to at least one of the measured parameters at a reporting
rate decoupled from the sampling rate that enables monitoring of
current energy usage, detecting a significant change in a measured
parameter, determining whether the significant change in the
measured parameter is caused by a change in energy usage, and
automatically transmitting, independent of the sampling rate and
the reporting rate, information related to the significant change
in the measured parameter caused by the change in energy usage
after detecting the significant change.
In an embodiment, automatically transmitting information related to
the significant change in the measured parameter caused by the
change in energy usage after detecting the significant change can
occur within 30 seconds after the detected change occurs. The
sampling rate can be between approximately 0.1 Hz and approximately
1 MHz, and the sampling rate is decoupled from the reporting rate
that enables monitoring of the current energy usage. The reporting
rate can be between approximately once per day and approximately
eight thousand times per second. The sampling rate and the
reporting rate may vary from one measured parameter to another. The
detected significant change can be approximately a 0.25% change in
the measured parameter or the detected significant change can be
user-defined. The rate of automatically transmitting information
may change based on the variability of the measured parameter. The
measured parameter can be selected from the group consisting of
light intensity, rotational speed, linear speed, temperature,
vibration, carbon dioxide, pressure, motion, flow, acceleration,
position, tension, torque, voltage, current, sound, and ultrasonic
frequencies. The measured current can be referenced to any of the
measured voltage phases for determination of power factor and phase
angle. The measured circuits can be of Delta configuration, Wye
configuration, or any combination thereof and in any sequence. The
voltage measurements can be of one or more phases, and the voltage
measurement of any phase can be referenced to the voltage
measurement of any other phase including one or more neutrals.
In an embodiment, the method further comprises outputting, based at
least in part on the measured parameter, a variable duty cycle
signal for load control of at least one electric circuit, wherein
the load control includes at least one of electric energy control
and carbon footprint control, and wherein the electric circuit is
selected from the group consisting of a lighting circuit, a motor
circuit, an air handling system, a pump, and an HVAC compressor
system. The measured parameter can be stored when it cannot be
automatically transmitted and a stored parameter can be transmitted
automatically when possible.
Further, in an embodiment, determining whether the significant
change in the measured parameter is caused by the change in energy
usage includes acquiring an additional sample of the measured
parameter, and determining whether the additional sample of the
measured parameter is proportional to the significant change of the
measured parameter, wherein when the additional sample of the
measured parameter is proportional to the significant change in the
measured parameter, the significant change in the measured
parameter is caused by the change in energy usage. The additional
sample can be acquired within 10 msec of detecting the significant
change in the measured parameter. The method further comprises
storing the significant change in the measured parameter when the
significant change in the measured parameter is caused by the
change in energy usage and disregarding the significant change in
the measured parameter when the additional sample of the measured
parameter is not proportional to the significant change in the
measured parameter.
According to a number of embodiments, the disclosure relates to a
system for measuring and analyzing energy efficiency of a facility
or facility subsystem. The system comprises a plurality of energy
measurement devices configured to measure one or more parameters
indicative of energy usage for a plurality of circuits,
sub-circuits, or systems wherein a sampling rate for measuring is
substantially continuous, a plurality of measurement devices
configured to measure one or more parameters indicative of the
energy efficiency of systems, wherein a sampling rate for measuring
is substantially continuous, a plurality of measurement devices
configured to measure one or more parameters indicative of the
environmental condition of systems and facilities, wherein a
sampling rate for measuring is substantially continuous, computer
hardware including at least one computer processor, and
computer-readable storage including computer-readable instructions
that, when executed by the computer processor, cause the computer
hardware to perform operations defined by the computer-executable
instructions. The computer-executable instructions include
automatically transmitting information related to at least one of
the measured parameters at a rate that enables monitoring of
current energy efficiency, automatically obtaining relevant
environmental conditions including weather data, detecting a
significant change in a measured parameter, determining whether the
significant change in the measured parameter is caused by a change
in energy efficiency, determining whether and the significant
change in the measured parameter caused a change in energy
efficiency, and automatically transmitting information related to
the significant change in the measured parameter caused by the
change in energy efficiency after detecting the significant
change.
In an embodiment, automatically transmitting information related to
the significant change in the measured parameter caused by the
change in energy efficiency after detecting the significant change
can occur within 30 seconds after the detected change occurs. The
sampling rate can be between approximately 0.1 Hz and approximately
1 MHz, and the sampling rate is independent of the rate that
enables monitoring of the current energy usage. The detected
significant change can be approximately a 0.25% change in the
measured parameter or the detected significant change can be user
defined. The rate of automatically transmitting information may
change based on the variability of the measured parameter. The
measured parameter can be selected from the group consisting of
light intensity, rotational speed, linear speed, temperature,
vibration, carbon dioxide, pressure, motion, flow, acceleration,
voltage, current, sound, and ultrasonic frequencies.
The computer-executable instructions further include, in an
embodiment, outputting, based at least in part on the measured
parameter, a variable duty cycle signal for load control of at
least one electric circuit, where the load control includes at
least one of electric energy control and carbon footprint control,
and wherein the electric circuit is selected from the group
consisting of a lighting circuit, a motor circuit, an air handling
system, and an HVAC compressor system. The computer-executable
instructions further include providing derived analysis of energy
required by a facility or facility subsystem, based in part on the
measured parameter that is selected from the group of measured
parameters consisting of building orientation, time of day, outside
air temperature, inside air temperature, reheat coil water
temperature, cold air temperature, CO2, and enthalpy of return air.
The computer-executable instructions further include a providing a
derived analysis of energy required by a facility or a facility
subsystem, based in part on a group of derived factors that are
selected from those factors that contribute to facility heat
loading and energy use including consisting of building occupancy,
time of day, day of the week, day of the year, vacation schedules,
lighting heat loads, and number of PC computers that are present in
the facility. The computer-executable instructions further include
outputting data, based at least in part on a comparison of the
measured parameter of energy use compared to the derived parameter
of energy required for a facility or facility subsystem consisting,
of at least one of an electric circuit, and a gas circuit, outside
temperature, and inside temperature, and time of day and facility
occupancy, and wherein the measured electric circuit, gas circuit,
CO2, return air enthalpy is selected from the group consisting a
lighting circuit, a motor circuit, an air handling system, an HVAC
reheat hot water coil system, and a HVAC compressor system. The
computer-executable instructions further include outputting of
data, based at least in part on a comparison of the measured
parameter of energy used and compared to the derived parameter of
energy required by a facility or subsystem from the group
consisting of a lighting circuit, a motor circuit, an air handling
system, and a HVAC compressor system. The computer-executable
instructions further include outputting data, based at least in
part on a comparison of the measured parameter of energy use
compared to the derived parameter of energy required for a facility
or subsystem where the difference of measured energy used versus
derived energy required by a facility or subsystem provides a
differential signal that is proportional to the difference in
measured energy used parameter versus derived energy parameter
required from the group consisting of a lighting circuit, a motor
circuit, an air handling system, a boiler reheat coil system, and a
HVAC compressor system. The computer-executable instructions
further include outputting substantially instantaneous demand
response energy load use data that is based at least in part on a
comparison of the measured parameter of energy use compared to the
derived parameter of energy required for a facility subsystem from
the group consisting of a lighting circuit, a motor circuit, an air
handling system, and an HVAC compressor system.
Further, in an embodiment, determining whether the significant
change in the measure parameter is caused by the change in energy
usage or energy required by a building or a building subsystem
includes acquiring an additional sample of the measured parameter,
and determining whether the additional sample of the measured
parameter is proportional to the significant change of the measured
parameter, wherein when the additional sample of the measured
parameter is proportional to the significant change in the measured
parameter, the significant change in the measured parameter is
caused by the change in energy efficiency. The additional sample
can be acquired within 10 msec of detecting the significant change
in the measured parameter. The computer-executable instructions
further include storing the significant change in the measured
parameter when the significant change in the measured parameter is
caused by the change in energy usage or a change in energy
required. The computer-executable instructions further include
disregarding the significant change in the measured parameter when
the additional sample of the measured parameter is not proportional
to the significant change in the measured parameter.
Certain other embodiments relate to a system for measuring,
analyzing and controlling energy usage of a facility or facility
subsystem. The system comprises a plurality of energy measurement
devices configured to measure one or more parameters indicative of
energy usage for a plurality of circuits, sub-circuits, or systems
where a sampling rate for measuring is substantially continuous, a
plurality of measurement devices configured to measure one or more
parameters indicative of the energy efficiency of systems, where a
sampling rate for measuring is substantially continuous, and a
plurality of measurement devices configured to measure one or more
parameters indicative of the environmental condition of systems and
facilities, wherein a sampling rate for measuring is substantially
continuous. The system further comprises computer hardware
including at least one computer processor, and computer-readable
storage including computer-readable instructions that, when
executed by the computer processor, cause the computer hardware to
perform operations defined by the computer-executable instructions.
The computer-executable instructions include automatically
transmitting information related to at least one of the measured
parameters at a rate that enables monitoring of current energy
efficiency, automatically obtaining relevant environmental
conditions including weather data, automatically determining
control sequence to maximize energy efficiency, automatically
determining control sequence to minimize demand usage at any time
without affecting operations and comfort, automatically
transmitting control commands to at least one system or equipment,
detecting a significant change in a measured parameter, determining
whether the significant change in the measured parameter is caused
by a change in energy usage, determining whether and the
significant change in the measured parameter caused a change in
energy efficiency, and automatically transmitting information
related to the significant change in the measured parameter caused
by the change in energy efficiency after detecting the significant
change.
In an embodiment, the computer-executable instructions further
include outputting, based at least in part on the measured
parameter, a variable duty cycle signal for load control of at
least one electric circuit, wherein the load control includes at
least one of electric energy control and carbon footprint control,
and where the electric circuit is selected from the group
consisting of lighting circuit, a motor circuit, an air handling
system, and an HVAC compressor system. The computer-executable
instructions further include outputting demand response energy load
use data that is based at least in part on a comparison of the
measured parameter of energy use compared to the derived parameter
of energy required for a facility subsystem for purposes of
providing an output signal that enables reduction in energy used in
one or more building subsystems consisting of a lighting circuit, a
motor circuit, an air handling system, an HVAC reheat coil system,
and an HVAC compressor system.
In an embodiment, the measured parameter includes at least one of
motor speed, motor temperature, motor vibration, belt tension,
motor balance, motor torque, motor power consumption, motor phase
imbalance, motor power factor, motor power quality, motor harmonic
energy, motor fundamental energy, facility demand reduction
requirements, utility demand reduction requirements, and parameters
upstream and downstream of a motor. In an embodiment, analyzed data
includes at least one of motor efficiency and motor maintenance
requirements. In another embodiment, the control command includes
at least one of turning the motor on, turning the motor off,
reducing motor speed, reducing motor frequency, and pulse width
modulation of motor power.
Additional Configurations of Embodiments of the Energy Management
System
In one arrangement, electrical power from the power distribution
grid enters the facility 104 through a main power bus into the
facility's power distribution system. The power distribution system
typically comprises a power distribution panel including main power
distribution bars, electrical circuits 218, 220, 222, and circuit
breakers. Examples of a power distribution panel are a main switch
board, a sub panel, a distribution panel/box, a motor control
center (MCC), and the like. In an embodiment, the energy management
system 102 is enclosed in an enclosure mounted adjacent to the
facility's power distribution panel and electrically connected to
the panel's electrical circuits 218, 220, 222 through circuit
breakers. In other embodiments, the energy management system 102 is
embedded in the facility's power distribution system.
In another embodiment, the energy management system 102 is embedded
in a circuit breaker have an integral measuring device 330, such as
a current sensor, a current transformer, a shunt resistor module,
or the like, and a wireless, wired or power line carrier (PLC)
communication and command module.
In other embodiments, the energy management system 102 is enclosed
in an enclosure mounted in the space to be monitored. In further
embodiments, the energy management system 102 can be embedded in
motors 220, 222, appliances, pumps 220, fans 222, lighting
fixtures, elevators, elevator motors, electrical equipment,
variable frequency devices, variable air volume valves,
thermostats, temperature sensors, computers, machinery, electric
vehicles, power supplies, generator controllers, or other
electrical equipment and appliances, such as power outlets, power
sockets, power strips, power extensions, power adapters, light
switches, motion sensors, gas sensors, security cameras, IR
detectors, load sensors, and the like.
Additional Features of Embodiments of the Energy Management
System
The energy management system 102 can further comprises one or more
of circuit protection, a circuit breaking capability, a power
factor correction capability, and a frequency shifting and
switching capability, such as currently employed by variable
frequency drives, Class D or Class E control circuits, and the
like, using high speed electronic switching devices, such as TRIAC
switches, MOSFET switches, solid state relays or any other high
speed high power switching devices, for example.
In other embodiments, the energy management system 102 further
comprises one or more of a wireless or wired communication module,
occupancy sensor, occupancy counter, light sensor, temperature
sensor, wireless thermostat, current sensor, gas sensor, heat
sensor, rechargeable battery backup, solar photovoltaic panel for
self-powered systems, LED displays, and the like.
Other embodiments of the energy management system 102 communicate
with other devices and/or instruments in the vicinity, such as, for
example, controlling/non-controlling and wired/wireless
thermostats, variable air volume (VAV) controllers, mechanical or
electrical shades, automatic door locks, door sensors, card
scanners, RFID devices, generator controller, and the like.
Other embodiments of the energy management system 102 can be part
of a mesh network in peer-to-peer, client-server, or master-slave
configuration and yet further embodiments can be a Plug & Play,
install and forget, stand alone measurement, communication, and
control system.
Additional embodiments of the energy management system 102 can
measure and analyze data from internal and external sensors
including current, voltage levels and waveforms, temperature,
vibration, motor speed, motor torque and mechanical load, and the
like. Other embodiments can calculate and communicate in real time
or near real time an efficiency rating of a motor 220, 222 or other
electrical equipment that may take into consideration an ambient
condition of the motor 220, 222 or other electrical equipment in
addition to the measured and analyzed data. The ambient condition
can be communicated to the device through the embedded
communication module, the analog inputs 206, or the digital inputs
206.
The embodiments of the method, technology, circuits, and algorithms
can be implemented, for example, on a circuit board with discrete
components such as integrated circuits (ICs), application specific
ICS (ASICs), field-programmable gate arrays (FPGAs), gate arrays,
and modules, or can be built into an ASIC, central processing unit
(CPU) 202, or system on a chip (SoC) for purposes of local or
remote digital measurement, analysis, communication, and control of
electric energy that is used by electrical systems, motors,
buildings, appliances, electric vehicles, and/or electric
transportation systems that are temporarily or permanently
connected to an electric grid, the envisioned "smart grid", or at a
point on a micro-grid, or in a residence, building, data center, or
commercial facility that uses electricity and that appears at any
point along an electric grid, micro grid, "smart grid", or at any
point in a power distribution system, including but not limited to
transformers, capacitors, and distribution panels.
Depending on the embodiment, certain acts, events, or functions of
any of the algorithms described herein can be performed in a
different sequence, can be added, merged, or left out altogether
(e.g., not all described acts or events are necessary for the
practice of the algorithm). Moreover, in certain embodiments, acts
or events can be performed concurrently, e.g., through
multi-threaded processing, interrupt processing, or multiple
processors or processor cores or on other parallel architectures,
rather than sequentially.
The various illustrative logical blocks, modules, and algorithm
steps described in connection with the embodiments disclosed herein
can be implemented as electronic hardware, computer software, or
combinations of both. To clearly illustrate this interchangeability
of hardware and software, various illustrative components, blocks,
modules, and steps have been described above generally in terms of
their functionality. Whether such functionality is implemented as
hardware or software depends upon the particular application and
design constraints imposed on the overall system. The described
functionality can be implemented in varying ways for each
particular application, but such implementation decisions should
not be interpreted as causing a departure from the scope of the
disclosure.
The various illustrative logical blocks and modules described in
connection with the embodiments disclosed herein can be implemented
or performed by a machine, such as a general purpose processor, a
digital signal processor (DSP), an ASIC, a FPGA or other
programmable logic device, discrete gate or transistor logic,
discrete hardware components, or any combination thereof designed
to perform the functions described herein. A general purpose
processor can be a microprocessor, but in the alternative, the
processor can be a controller, microcontroller, or state machine,
combinations of the same, or the like. A processor can also be
implemented as a combination of computing devices, e.g., a
combination of a DSP and a microprocessor, a plurality of
microprocessors, one or more microprocessors in conjunction with a
DSP core, or any other such configuration.
The steps of a method, process, or algorithm described in
connection with the embodiments disclosed herein can be embodied
directly in hardware, in a software module executed by a processor,
or in a combination of the two. A software module can reside in RAM
memory, flash memory, ROM memory, EPROM memory, EEPROM memory,
registers, hard disk, a removable disk, a CD-ROM, or any other form
of computer-readable storage medium known in the art. An exemplary
storage medium can be coupled to the processor such that the
processor can read information from, and write information to, the
storage medium. In the alternative, the storage medium can be
integral to the processor. The processor and the storage medium can
reside in an ASIC. The ASIC can reside in the energy management
system 102. In the alternative, the processor and the storage
medium can reside as discrete components in the energy management
system 102.
The above detailed description of certain embodiments is not
intended to be exhaustive or to limit the invention to the precise
form disclosed above. While specific embodiments of, and examples
for, the invention are described above for illustrative purposes,
various equivalent modifications are possible within the scope of
the invention, as those ordinary skilled in the relevant art will
recognize. For example, while processes or blocks are presented in
a given order, alternative embodiments may perform routines having
steps, or employ systems having blocks, in a different order, and
some processes or blocks may be deleted, moved, added, subdivided,
combined, and/or modified. Each of these processes or blocks may be
implemented in a variety of different ways. Also, while processes
or blocks are at times shown as being performed in series, these
processes or blocks may instead be performed in parallel, or may be
performed at different times.
Unless the context clearly requires otherwise, throughout the
description and the claims, the words "comprise," "comprising," and
the like are to be construed in an inclusive sense, as opposed to
an exclusive or exhaustive sense; that is to say, in the sense of
"including, but not limited to." The words "coupled" or connected",
as generally used herein, refer to two or more elements that may be
either directly connected, or connected by way of one or more
intermediate elements. Additionally, the words "herein," "above,"
"below," and words of similar import, when used in this
application, shall refer to this application as a whole and not to
any particular portions of this application. Where the context
permits, words in the above Detailed Description using the singular
or plural number may also include the plural or singular number
respectively. The word "or" in reference to a list of two or more
items, that word covers all of the following interpretations of the
word: any of the items in the list, all of the items in the list,
and any combination of the items in the list.
Moreover, conditional language used herein, such as, among others,
"can," "could," "might," "may," "e.g.," "for example," "such as"
and the like, unless specifically stated otherwise, or otherwise
understood within the context as used, is generally intended to
convey that certain embodiments include, while other embodiments do
not include, certain features, elements and/or states. Thus, such
conditional language is not generally intended to imply that
features, elements and/or states are in any way required for one or
more embodiments or that one or more embodiments necessarily
include logic for deciding, with or without author input or
prompting, whether these features, elements and/or states are
included or are to be performed in any particular embodiment.
The teachings of the invention provided herein can be applied to
other systems, not necessarily the systems described above. The
elements and acts of the various embodiments described above can be
combined to provide further embodiments.
While certain embodiments of the inventions have been described,
these embodiments have been presented by way of example only, and
are not intended to limit the scope of the disclosure. Indeed, the
novel methods and systems described herein may be embodied in a
variety of other forms; furthermore, various omissions,
substitutions and changes in the form of the methods and systems
described herein may be made without departing from the spirit of
the disclosure. The accompanying claims and their equivalents are
intended to cover such forms or modifications as would fall within
the scope and spirit of the disclosure.
* * * * *
References